What is he best known for?
The fields of study he is best known for:
- Computer network
- Operating system
- Artificial intelligence
Real-time computing, Computer network, Wireless sensor network, Wireless and Distributed computing are his primary areas of study.
His studies in Real-time computing integrate themes in fields like Tracking, Physical layer, Simulation, Embedded system and Channel state information.
His Computer network research integrates issues from Scalability, Layer, The Internet and Identification.
His Wireless sensor network research is multidisciplinary, relying on both Key distribution in wireless sensor networks, Visual sensor network, Wireless network and Ranging.
Yunhao Liu has researched Wireless in several fields, including Mobile radio, Software deployment, Mobile computing and Leverage.
His study in Distributed computing is interdisciplinary in nature, drawing from both Overlay network, Wireless ad hoc network, Network topology, Node and Flooding.
His most cited work include:
- LANDMARC: indoor location sensing using active RFID (1736 citations)
- Big Data: A Survey (1645 citations)
- LANDMARC: indoor location sensing using active RFID (659 citations)
What are the main themes of his work throughout his whole career to date?
Yunhao Liu spends much of his time researching Computer network, Wireless sensor network, Distributed computing, Real-time computing and Wireless.
His Computer network research incorporates themes from Wireless ad hoc network, Scalability, Throughput and Wireless network.
His research in Wireless sensor network intersects with topics in Energy consumption, Key distribution in wireless sensor networks, Mobile wireless sensor network, Node and Testbed.
His studies deal with areas such as Network topology, Overlay network, Topology and Flooding as well as Distributed computing.
His work deals with themes such as Ranging, Efficient energy use, Embedded system and Simulation, which intersect with Real-time computing.
His research ties Mobile computing and Wireless together.
He most often published in these fields:
- Computer network (34.12%)
- Wireless sensor network (28.38%)
- Distributed computing (24.66%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (9.97%)
- Real-time computing (21.79%)
- Key (7.94%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Real-time computing, Key, Computer vision and Wireless.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning and Interface.
Yunhao Liu performs integrative Real-time computing and Doppler effect research in his work.
He combines subjects such as Telecommunications, Network packet and Big data with his study of Key.
His Computer vision research focuses on subjects like Mobile device, which are linked to Match moving.
His work in Wireless covers topics such as Crowdsourcing which are related to areas like Optimization problem.
Between 2017 and 2021, his most popular works were:
- Widar2.0: Passive Human Tracking with a Single Wi-Fi Link (92 citations)
- Zero-Effort Cross-Domain Gesture Recognition with Wi-Fi (56 citations)
- On Reliable Task Assignment for Spatial Crowdsourcing (37 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Computer network
- Artificial intelligence
His main research concerns Artificial intelligence, Real-time computing, Key, Computer vision and Robustness.
Yunhao Liu has included themes like Data science and Code in his Artificial intelligence study.
Yunhao Liu incorporates Real-time computing and Doppler effect in his studies.
His Key research is multidisciplinary, incorporating perspectives in Computer hardware, Leverage, Network packet, Throughput and Fingerprint.
Wireless is closely connected to Embedded system in his research, which is encompassed under the umbrella topic of Inertial measurement unit.
His Radio frequency research is multidisciplinary, incorporating elements of Computer security and Base station.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
